Box's M test
Box's M test is a statistical test used to check whether multiple variance-covariance matrices are equal. The test is commonly used to test the assumption of homogeneity of variances and covariances in linear discriminant analysis. It is named after George E. P. Box.
Box's M test is susceptible to errors if the data does not meet model assumptions or if the sample size is too large or small.[1] Box's M test is especially prone to error if the data does not meet the assumption of multivariate normality.[2]
See also
References
- ^ Rebecca M. Warner (2013). Applied Statistics: From Bivariate Through Multivariate Techniques: From Bivariate Through Multivariate Techniques. SAGE. p. 778. ISBN 978-1-4129-9134-6.
- ^ Bryan F.J. Manly (6 July 2004). Multivariate Statistical Methods: A Primer, Third Edition. CRC Press. p. 54. ISBN 978-1-58488-414-9.
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